Publications de Fikret Isik Karahanoglu

Mood disorders disrupt the functional dynamics, not spatial organization of brain resting state networks

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu

Spontaneous fluctuations in the blood oxygenation level dependent signal measured through resting-state functional magnetic resonance imaging have been corroborated to aggregate into multiple functional networks. Abnormal resting brain activity is observed ...

ELSEVIER SCI LTD2021

Deconvolution of Sustained Neural Activity From Large-Scale Calcium Imaging Data

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

Recent technological advances in light-sheet microscopy make it possible to perform whole-brain functional imaging at the cellular level with the use of Ca2+ indicators. The outstanding spatial extent and resolution of this type of data open unique opportu ...

Institute of Electrical and Electronics Engineers2020

Bold Signal Deconvolution Under Uncertain HÆModynamics: A Semi-Blind Approach

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

The investigation of spontaneous and evoked neuronal activity from functional Magnetic Resonance Imaging (fMRI) data has come to play a significant role in deepening our understanding of brain function. As this research trend continues, activity detection ...

IEEE2019

Large-Scale Brain Network Dynamics Provide a Measure of Psychosis and Anxiety in 22q11.2 Deletion Syndrome Daniela

Dimitri Nestor Alice Van De Ville, Marie Schaer, Fikret Isik Karahanoglu, Maria Carmela Padula

BACKGROUND: Prodromal positive psychotic symptoms and anxiety are two strong risk factors for schizophrenia in 22q11.2 deletion syndrome (22q11DS). The analysis of large-scale brain network dynamics during rest is promising to investigate aberrant brain fu ...

ELSEVIER2019

Robust Recovery of Temporal Overlap Between Network Activity Using Transient-Informed Spatio-Temporal Regression

Dimitri Nestor Alice Van De Ville, Marie Schaer, Fikret Isik Karahanoglu, Thomas William Arthur Bolton, Daniela Maria Zöller

Functional magnetic resonance imaging is a non-invasive tomographic imaging modality that has provided insights into system-level brain function. New analysis methods are emerging to study the dynamic behavior of brain activity. The innovation-driven co-ac ...

Institute of Electrical and Electronics Engineers2019

Quantification Of Resting-State Fmri Networks Driven By Hemodynamically Informed Spatiotemporal Regularization

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

The brain's spontaneous fluctuations measured by functional magnetic resonance imaging during rest cluster into recurrent activity patterns known as resting-state networks (RSNs). The spatial organization of RSNs in health and disease has been immensely in ...

IEEE2018

Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder

Djalel Eddine Meskaldji, Fikret Isik Karahanoglu

Autism Spectrum Disorder (ASD) is thought to reflect disrupted development of brain connectivity characterized by white matter abnormalities and dyscoordination of activity across brain regions that give rise to core features. But there is little consensus ...

2018

Total-activation regularized deconvolution of resting-state fMRI leads to reproducible networks with spatial overlap

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu

Spontaneous activations in resting-state fMRI have been shown to corroborate recurrent intrinsic functional networks. Recent studies have explored integration of brain function in terms of spatially overlapping networks. We have proposed a method to recove ...

IEEE2016

Schizophrenia patients and 22q11.2 deletion syndrome adolescents at risk express the same deviant patterns of resting state EEG microstates: A candidate endophenotype of schizophrenia

Dimitri Nestor Alice Van De Ville, Michael Herzog, Fikret Isik Karahanoglu, Maya Roinishvili, Maude Schneider

Schizophrenia is a complex psychiatric disorder and many of the factors contributing to its pathogenesis are poorly understood. In addition, identifying reliable neurophysiological markers would improve diagnosis and early identification of this disease. T ...

2015

Functional Networks Driven by Transient Activity in Resting-State of Mood Disorders

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu

Elsevier Science Inc2015

Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu

Dynamics of resting-state functional magnetic resonance imaging (fMRI) provide a new window onto the organizational principles of brain function. Using state-of-the-art signal processing techniques, we extract innovation-driven co-activation patterns (iCAP ...

Nature Publishing Group2015

Spatial Mapping Of Interictal Epileptic Discharges In Fmri With Total Activation

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu

During the monitoring of pharmacoresistant epilepsy patients prior to surgery, interictal epileptic discharges (IEDs) are analyzed to locate possible sources of epileptic activity. In order to compensate low spatial resolution of EEG, simultaneous EEG-fMRI ...

Ieee2013

Sparsity-Promoting Spatiotemporal Regularization for Data Mining in Functional Magnetic Resonance Imaging

Fikret Isik Karahanoglu

Magnetic resonance imaging (MRI) has opened unprecedented avenues to observe the human brain non-invasively. In particular, for about two decades, functional MRI (fMRI) has enabled to monitor brain function using the blood-oxygen-level-dependent (BOLD) con ...

EPFL2013

Total activation: fMRI deconvolution through spatio-temporal regularization

Dimitri Nestor Alice Van De Ville, François Lazeyras, Fikret Isik Karahanoglu

Confirmatory approaches to fMRI data analysis look for evidence for the presence of pre-defined regressors modeling contributions to the voxel time series, including the BOLD response following neuronal activation. As more complicated questions arise about ...

Elsevier2013

A Signal Processing Approach to Generalized 1-D Total Variation

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Ilker Bayram

Total variation (TV) is a powerful method that brings great benefit for edge-preserving regularization. Despite being widely employed in image processing, it has restricted applicability for 1-D signal processing since piecewise-constant signals form a rat ...

Institute of Electrical and Electronics Engineers2011